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Failure Probability Analysis Based on FRI Model for Stress Corrosion Cracking Growth Introducing Residual Stress Distribution by Weld

[+] Author Affiliations
Noriyoshi Maeda

Japan Nuclear Energy Safety Organization (JNES), Tokyo, Japan

Tetsuo Shoji

Tohoku University, Sendai, Japan

Paper No. PVP2012-78748, pp. 393-402; 10 pages
doi:10.1115/PVP2012-78748
From:
  • ASME 2012 Pressure Vessels and Piping Conference
  • Volume 1: Codes and Standards
  • Toronto, Ontario, Canada, July 15–19, 2012
  • Conference Sponsors: Pressure Vessels and Piping Division
  • ISBN: 978-0-7918-5500-3
  • Copyright © 2012 by ASME

abstract

Failure probability of welds by stress corrosion cracking (SCC) in austenitic stainless steel piping is analyzed by a probabilistic fracture mechanics (PFM) approach based on an electro-chemical crack growth model (FRI model, where FRI stands for “Fracture and Reliability Research Institute” of Tohoku University in Japan). In this model, crack growth rate da/dt, where a is crack depth, is anticipated as the rate of chemical corrosion process defined by electro-chemical Coulomb’s law. The process is also related to the strain rate at the crack tip, taking the small scale yielding into consideration. Compared to the mechanical crack growth equation like the power law for SCC, FRI model can introduce many parameters affecting the generation and break of protective film on the crack surface such as electric current associated with corrosion, the frequency of protective film break and mechanical parameters such as the stress intensity factor K and its change with time dK/dt. Derived transcendental equation is transformed into non-dimensional form, and then solved numerically by iterative method. The extension of surface crack by SCC under residual stress field is simulated by developing the stress distribution in polynomial form following ASME section XI appendix A. This simulation scheme is introduced into PFM framework to derive the failure probability of austenitic stainless steel piping in nuclear power plants to be used in developing a risk-informed inservice inspection (RI-ISI) program.

Copyright © 2012 by ASME

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